{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e97f4fa7-bde6-4de4-8e94-b3b56c43754e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 用geopandas读取shapefile\n",
    "# 用geopandas可视化shapefile\n",
    "# 用shapely创建新的空间要素：点，线，面\n",
    "# 用geopandas可视化新建的空间要素\n",
    "# 利用geopandas输出shapefile"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "83fa13ea-6414-42f6-b09e-4917c9d2a1ba",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-08T03:40:51.892736Z",
     "iopub.status.busy": "2021-06-08T03:40:51.892438Z",
     "iopub.status.idle": "2021-06-08T03:40:53.394704Z",
     "shell.execute_reply": "2021-06-08T03:40:53.394050Z",
     "shell.execute_reply.started": "2021-06-08T03:40:51.892669Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "import geopandas as gpd\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "8c5b2063-74c1-49eb-8a30-b74d5918182c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-08T03:43:53.841813Z",
     "iopub.status.busy": "2021-06-08T03:43:53.841566Z",
     "iopub.status.idle": "2021-06-08T03:43:53.856280Z",
     "shell.execute_reply": "2021-06-08T03:43:53.855018Z",
     "shell.execute_reply.started": "2021-06-08T03:43:53.841788Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# 读取shapefile\n",
    "data = gpd.GeoDataFrame.from_file(r'../data/Shapefiles/sz.shp', encoding = 'utf-8')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "c6915144-2fb6-40e7-8220-570593fcad22",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-08T03:50:49.619471Z",
     "iopub.status.busy": "2021-06-08T03:50:49.619167Z",
     "iopub.status.idle": "2021-06-08T03:50:49.773458Z",
     "shell.execute_reply": "2021-06-08T03:50:49.772825Z",
     "shell.execute_reply.started": "2021-06-08T03:50:49.619412Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 可视化\n",
    "data.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "395e6d27-6627-43f0-952f-42c6fb39806f",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-08T03:49:10.740962Z",
     "iopub.status.busy": "2021-06-08T03:49:10.740711Z",
     "iopub.status.idle": "2021-06-08T03:49:10.780483Z",
     "shell.execute_reply": "2021-06-08T03:49:10.779704Z",
     "shell.execute_reply.started": "2021-06-08T03:49:10.740936Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>centroid_x</th>\n",
       "      <th>centroid_y</th>\n",
       "      <th>qh</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>114.143157</td>\n",
       "      <td>22.577605</td>\n",
       "      <td>罗湖</td>\n",
       "      <td>POLYGON ((114.10006 22.53431, 114.09969 22.535...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>114.041535</td>\n",
       "      <td>22.546180</td>\n",
       "      <td>福田</td>\n",
       "      <td>POLYGON ((113.98578 22.51348, 113.98558 22.523...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>114.270206</td>\n",
       "      <td>22.596432</td>\n",
       "      <td>盐田</td>\n",
       "      <td>POLYGON ((114.22772 22.54290, 114.22643 22.543...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>113.851387</td>\n",
       "      <td>22.679120</td>\n",
       "      <td>宝安</td>\n",
       "      <td>MULTIPOLYGON (((113.81831 22.54676, 113.81816 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>113.926290</td>\n",
       "      <td>22.766157</td>\n",
       "      <td>光明</td>\n",
       "      <td>POLYGON ((113.98587 22.80304, 113.98605 22.802...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>114.356936</td>\n",
       "      <td>22.691020</td>\n",
       "      <td>坪山</td>\n",
       "      <td>POLYGON ((114.42581 22.66510, 114.42470 22.664...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>114.029687</td>\n",
       "      <td>22.686910</td>\n",
       "      <td>龙华</td>\n",
       "      <td>POLYGON ((114.10825 22.72368, 114.10785 22.723...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>113.930714</td>\n",
       "      <td>22.544103</td>\n",
       "      <td>南山</td>\n",
       "      <td>MULTIPOLYGON (((113.81491 22.39929, 113.80914 ...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   centroid_x  centroid_y  qh  \\\n",
       "0  114.143157   22.577605  罗湖   \n",
       "1  114.041535   22.546180  福田   \n",
       "2  114.270206   22.596432  盐田   \n",
       "3  113.851387   22.679120  宝安   \n",
       "4  113.926290   22.766157  光明   \n",
       "5  114.356936   22.691020  坪山   \n",
       "6  114.029687   22.686910  龙华   \n",
       "7  113.930714   22.544103  南山   \n",
       "\n",
       "                                            geometry  \n",
       "0  POLYGON ((114.10006 22.53431, 114.09969 22.535...  \n",
       "1  POLYGON ((113.98578 22.51348, 113.98558 22.523...  \n",
       "2  POLYGON ((114.22772 22.54290, 114.22643 22.543...  \n",
       "3  MULTIPOLYGON (((113.81831 22.54676, 113.81816 ...  \n",
       "4  POLYGON ((113.98587 22.80304, 113.98605 22.802...  \n",
       "5  POLYGON ((114.42581 22.66510, 114.42470 22.664...  \n",
       "6  POLYGON ((114.10825 22.72368, 114.10785 22.723...  \n",
       "7  MULTIPOLYGON (((113.81491 22.39929, 113.80914 ...  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 查看数据结构\n",
    "data.head(8)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "8a1dfae1-3c92-41d5-bb88-ef1114950be9",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-08T04:01:45.680105Z",
     "iopub.status.busy": "2021-06-08T04:01:45.679872Z",
     "iopub.status.idle": "2021-06-08T04:01:45.684117Z",
     "shell.execute_reply": "2021-06-08T04:01:45.682922Z",
     "shell.execute_reply.started": "2021-06-08T04:01:45.680080Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# 创建空间要素\n",
    "lat1 = 22.447837\n",
    "lng1 = 113.75194\n",
    "lat2 = 22.864748\n",
    "lng2 = 114.624187\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "75d3cb0f-bacc-4fc9-ad9b-7575bc9d3057",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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